Invention Grant
- Patent Title: Runtime extension for neural network training with heterogeneous memory
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Application No.: US16194958Application Date: 2018-11-19
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Publication No.: US11775799B2Publication Date: 2023-10-03
- Inventor: Georgios Mappouras , Amin Farmahini-Farahani , Sudhanva Gurumurthi , Abhinav Vishnu , Gabriel H. Loh
- Applicant: Advanced Micro Devices, Inc.
- Applicant Address: US CA Santa Clara
- Assignee: Advanced Micro Devices, Inc.
- Current Assignee: Advanced Micro Devices, Inc.
- Current Assignee Address: US CA Santa Clara
- Agency: KOWERT HOOD MUNYON RANKIN AND GOETZEL PC
- Agent Rory D. Rankin
- Main IPC: G06N20/10
- IPC: G06N20/10 ; G06N3/04 ; G06F9/54 ; G06F9/445 ; G06N3/084

Abstract:
Systems, apparatuses, and methods for managing buffers in a neural network implementation with heterogeneous memory are disclosed. A system includes a neural network coupled to a first memory and a second memory. The first memory is a relatively low-capacity, high-bandwidth memory while the second memory is a relatively high-capacity, low-bandwidth memory. During a forward propagation pass of the neural network, a run-time manager monitors the usage of the buffers for the various layers of the neural network. During a backward propagation pass of the neural network, the run-time manager determines how to move the buffers between the first and second memories based on the monitored buffer usage during the forward propagation pass. As a result, the run-time manager is able to reduce memory access latency for the layers of the neural network during the backward propagation pass.
Public/Granted literature
- US20200042859A1 RUNTIME EXTENSION FOR NEURAL NETWORK TRAINING WITH HETEROGENEOUS MEMORY Public/Granted day:2020-02-06
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